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Classification of CDMA Systems



• Synchronous: transmissions of users are

synchronized down to chip levels (difficult,

but permits orthogonal transmission).

• Asynchronous systems



Classification of CDMA Sequences

• Orthogonal Sequences

• Pseudonoise (PN) sequences

1

Desirable Properties of Sequences



• Good autocorrelation (for synchronization

and synchronous CDMA)

• Low crosscorrelation (for low multiple

access interference)

• Availability of large number of codes







2

Autocorrelation

• Degree of correspondence between a sequence and

a phase-shifted replica of itself.

N

C ( k )   an a n  k

n 1

For example let N=5, and {ak }  {1,1,1,1,1}

Then C(0)= 5

C(1)=-1-1-1+1-1=-3

C(2)=1+1+1-1-1=1

C(3)=1-1-1+1+1=1

C(4)=-1-1+1-1-1=-3

C(5)=C(0)=5

3

Cross correlation

• Degree of agreement between two different

sequences. N

R( k )   anbn  k

n 1

E.g, let {ak }  {1,1,1,1,1} {bk }  {1,1,1,1,1}

Then R(0)= 1+1-1-1-1=-1

R(1)=-1+1-1+1-1=-1

R(2)=-1+1+1+1+1=3

R(3)=1-1-1+1+1=1

R(4)=-1-1+1-1+1=-1

R(5)=R(0)=-1

4

Properties of Random Sequences

1. Relative frequencies of 0 and 1 are each 1/2

2. Run length like coin flipping

1/2 with length 1

1/4 with length 2

1/8 with length 3

1/2n with length n

3. If the sequence is shifted by any number of

elements, the resulting sequence will have equal

number of agreements and disagreements with the

original sequence.

5

Max Length PN Sequence Generator

ai 1ai 2 ai 3

1 0 0

0 1 0

1 0 1

1 1 0

1 1 1

ai 1 ai  2 ai  3

0 1 1

0 0 1

---------

1 0 0

0 1 0

6

Number of M Sequences

Shift reg. Length (n) Seq. Length N  2  1 # of sequences

n



2 3 1

3 7 2

4 15 2

5 31 6

6 63 6

7 127 16

8 255 16

9 511 48

10 1023 60

11 2047 176

12 4095 144

13 8191 630

14 16,383 756

15 32,767 1800

16 65,535 2048

17 131,071 7710

18 262,143 8064

19 524,287 27,594

20 1,048,575 24,000



7

Gold Codes

M-seq. 1

1 2 3 4 5









1 2 3 4 5

M-seq. 2

Sequence 1: 1111100011011101010000100101100

Sequence 2: 1111100100110000101101010001110

0 shift combination: 0000000111101101111101110100010

1 shift combination: 0000101010111100001010000110001



30 shift combination:1000010001000101000110001101011 8

Properties of Orthogonal Sequences



• When two orthogonal sequences are

multiplied and then integrated (summed),

the result is zero. Therefore if they are used

as for channelization, theoretically there is

no MAI (except due to multipath and sync).

• Autocorrelation properties of orthogonal

sequences usually are not good.



9

Walsh-Hadamard Codes

0 0 

H1  [0] H2   

0 1 

0 0 0 0 

0 1 0 1  H N H N 

H4    H 2N   

0 0 1 1  H N H N 

 

0 1 1 0 

Replace zeros by -1 and observe that

the sum of products of two rows is zero.

Shifted versions may not be orthogonal.

10

Walsh Sequences of Order 16

W0 = 00000000 00000000 W8 = 01100110 01100110

W1 = 00000000 11111111 W9 = 01100110 10011001

W2 = 00001111 11110000 W10 = 01101001 10010110

W3 = 00001111 00001111 W11 = 01101001 01101001

W4 = 00111100 00111100 W12 = 01011010 01011010

W5 = 00111100 11000011 W13 = 01011010 10100101

W6 = 00110011 11001100 W14 = 01010101 10101010

W7 = 00110011 00110011 W15 = 01010101 01010101





11

Variable Length Orthogonal Codes

C8 (1)

C4 (1)  {1,1,1,1}

C2 (1)  {1,1} C8 (2)

C8 (3)

C4 (2)  {1,1,1,1}

C8 (4)

C1 (1)  {1}

C8 (5)

C4 (3)  {1,1,1,1}

C8 (6)

C2 (2)  {1,1}

C8 (7)

C4 (4)  {1,1,1,1}

C8 (8)

SF=1 SF=2 SF=4 SF=8

SF: spreading factor 12

Spreading For Forward Traffic

Channel

Base PN

Walsh 1 code

User 1

data







Walsh N S Modulation

User N

data







13

Spreading For Reverse Traffic

Channel

data dependent PN code 1

Walsh

User 1

data Modulation

Spread



data dependent

Walsh PN code N

User N

data Spread Modulation





14

Advantage of Power as

the common resource

• For handling mixed services and variable

bit rate demands, allocate power to ensure

that maximum interference is not exceeded.

• Physical channel allocation remains

unchanged although bit rate might change.

(reallocation of codes, time slots,

frequencies etc. not needed).



15

Example of power as the common resource:

multiplexing variable bit-rate users









16

DS-CDMA BER Performance

Assuming random binary sequences, for (U  1)

simultaneous users,

L N O

SNR = M

U

P 0

1





3N 2 E Q

N b



Here, N  number of chips per bit (sequence length)

Pb  QcSNR h

With carefully selected sequences,

the performance can be better.

17

Simplified Capacity (CDMA)





In CDMA the total noise density is

Eb Rb

N o  N o  Io  N o  U

'



Ws

Eb Eb Eb

 ' 

No  Io No N  U Eb Rb

o

Ws





18

Processing Gain

In most practical cases the thermal noise No is

negligible in comparison to mutual interference

(also called self - noise). Then

Eb Eb 1 Gp

  U

No N  U Eb Rb U Rb

' Eb

o '

Ws Ws No

Ws Rc

  Gp is known as the processing gain

Rb Rb

Notice that here the minimum Nyquist bandwidth

is assumed for Ws (while Rappaport assumes twice

the minimum bandwidth).

19

Voice activity

If the carrier is turned off when the speaker is

silent, the self-noise reduces from

U Eb Rb/Ws

to

V U Eb Rb/Ws

where voice activity factor V is typically 0.35

to 0.4.



20

Example

(a)A CDMA system uses direct-sequence BPSK modulation

with a data rate R= 5 kbps. Assume 30 equal power data

users. Ignore the thermal noise. Determine the minimum chip

rate to obtain a BER of 10-5.

BER 10-5 requires an Eb/No of

approximately 10.



Gp Gp

U=  30   Gp  300

Eb 10

'

No

This means a chip rate of

Rc  5  300  1.5Mcps







21

Example (ctd)

(b) Repeat the calculations if 15 users are data the

other 15 users are voice users with voice activity

factor of 0.4.

•15 voice activated users are equivalent to

0.4x15=6 users, then the total is 21 users

Gp Gp

U=  21   G p  210

Eb 10

N o'

This means a chip rate of

Rc  5  210  105Mcps

.



22



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